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What is Snowflake Data Warehouse

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Previously, setting up a data warehouse used to involve purchasing a costly, custom-built hardware appliance and installing it in your data center. Snowflake, on the other hand, is a data warehouse that is available as software-as-a-service (SaaS).

It’s built from the ground up to be a cloud and provides the flexibility and efficiency that a typical data warehouse just cannot offer.

This article will explain what Snowflake Data Warehouse is, how it works, and the major features of this revolutionary technology.

Table of Content - Snowflake Data Warehouse 

➤ What is a Snowflake Data Warehouse

➤ How does Snowflake Data warehouse work?

➤ Snowflake Architecture

➤ Snowflake’s Differentiating Features from Other Cloud Data Warehouses

➤ Snowflake's Most Important Use Cases

➤ What type of database is Snowflake?

➤ Snowflake data warehouse pros and cons

What is a Snowflake Data Warehouse?

Snowflake is a cloud-based data warehouse that runs on Amazon Web Services or Microsoft Azure. It's great for enterprises that don't want to devote resources to the setup, maintenance, and support of in-house servers because there's no hardware or software to choose, install, configure, or manage.

Snowflake's design and data exchange capabilities, however, set it distinct. Customers can utilize and pay for storage and computing separately thanks to the Snowflake architecture, which provides storage and computation to independently scale. Furthermore, the sharing feature enables enterprises to instantly communicate controlled and secure data in real-time. You can learn more in Mindmajix’s Snowflake Online Training.

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How does Snowflake Data Warehouse work?

Snowflake has a lot of cool capabilities, but one of the most impressive is the ability to create an endless quantity of virtual warehouses (each efficiently an independent MPP cluster). As seen in the picture below, users can execute an endless number of independent workloads against the same data without fear of contention.

How does snowflake data warehouse work

Furthermore, each warehouse can be scaled from a single node extra-small cluster to a gigantic 128-node monster in milliseconds. Users won't have to put up with subpar performance because the machine's size may be modified during the day to match the workload. Lastly, in addition to scaling up for greater data volumes, it's also possible to scale out to handle large numbers of users automatically.

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Snowflake Architecture

The levels in the Snowflake service are depicted in the diagram below:

1. Cloud Service Layer:

This covers infrastructure, transaction management, SQL performance optimization, security, and metadata, as well as providing database connectivity. The cloud services layer organizes the entire system and uses ANSI SQL.

2. Compute Services Layer:

Hosts an almost infinite number of virtual warehouses, each of which is made up of a cluster of database servers that execute SQL operations. Despite the fact that the virtual warehouse is made up of CPUs, memory, and SSD storage, this is only a transitory storage layer.

3. Cloud Storage Layer:

Provides an inexhaustible source of long-term data storage. All data is saved in the cloud and is automatically copied to three different data centers, providing a disaster recovery layer built-in.

Although virtual warehouses can be started and stopped manually, the layers of the architecture work transparently to service end-user SQL queries. You can learn more about Snowflake Architecture.

Snowflake Architecture

Read these latest Snowflake Interview Questions that help you grab the high-paying job

Snowflake’s Differentiating Features from Other Cloud Data Warehouses

  • Snowflake is a cloud-based data warehouse that uses a subscription-based model with storage and computing running independently. Snowflake's technology uses elastic storage to automatically use hot/cold storage strategies to reduce costs, and scalable computing eliminates the usual concurrency limits that other warehouse options impose.
  • Snowflake's data warehouse is cloud-agonistic, allowing customers to use several clouds. Snowflake is accessible on Microsoft Azure, Google Cloud, and Amazon Web Services at the moment.
  • Snowflake saves both structured and semi-structured data and converts it to a SQL-compatible format.
  • Users can query data quickly without altering the underlying data set and receive data that is closer to real-time.
  • Snowflake's customizable cloud server solution decentralizes data, allowing each stakeholder or group within an organization to access specific data sets without the need for lengthy data transfers.
  • The company's services are available on-demand, allowing users to choose the amount of computation and storage they require before paying for it on a per-use or monthly fixed-rate basis. Because of Snowflake's flexible payment structure, compute and storage may be turned on and off as needed for certain instances and projects without incurring long-term costs.

Snowflake’s Differentiating Features

Snowflake's Most Important Use Cases

Snowflake's scalable architecture and simple querying make it an excellent tool for businesses that are just getting started with the data-driven paradigm.

The platform's usability and adaptability make it a powerful tool for businesses looking to test new systems, build their own analytical models, or try out multiple techniques to meet their data analysis and business intelligence needs.

  • Ad hoc analysis: Snowflake allows users to design their own queries. Snowflake's virtual warehousing enables users to create their own databases using both live and cached data, resulting in faster queries and more near-real-time BI insights.
  • Embedded Analytics. Snowflake provides embedded analytics applications with the elasticity, flexibility, and scalability they require.
Related Article: Difference between Snowflake vs Databricks

What type of database is Snowflake?

Snowflake was designed from the ground up to be a full-featured SQL database. It's a columnar-stored relational database that works well with Excel, Sau, and a variety of other tools that end-users are familiar with. Snowflake has its own query tool and supports multi-statement transactions, role-based security, windowing functions, full DML, and all other SQL database features.

Snowflake data warehouse pros and cons

The benefits of Snowflake cloud-based data warehousing have been thoroughly explored.

  • Performance and speed: Because of the cloud's elasticity, you can scale up your virtual warehouse to take advantage of more compute resources if you need to load data faster or perform a large number of queries. After that, you can scale the virtual warehouse and only pay for the time you used it.
  • Accessibility and concurrency: When too many queries compete for resources in a typical data warehouse with a high number of users or use cases, you may suffer concurrency difficulties (such as delays or failures).flake's innovative multicluster architecture solves concurrency issues: Virtual warehouse queries never affect queries from other virtual warehouses, and individually virtual warehouses can scale up or down as needed. Without having to wait for other loading and processing processes to finish, data analysts and data scientists may acquire what they need when they need it.
  • Software Upgrades: Upgrades to the software are no longer required. Snowflake is delivered as a software service, thus changes to the operating system and database are applied silently and transparently.
  • Tuning and Maintenance: This is no longer an issue because Snowflake does not support indexes, and there is no need to adjust the database aside from a few well-documented best practices. There are few requirements for DBA resources because the system is designed to be simple.
  • Security and availability: Snowflake is designed to run constantly and withstand network and component failures with the least impact on clients, and it is dispersed across availability zones of the platform on which it runs – either AWS or Azure. It is SOC 2 Type II certified, and it offers additional security features such as PHI data support for HIPAA clients and encryption across all network connections.
  • Data exchange is seamless: Snowflake's architecture allows users to share data with one another. It also enables businesses to share data with anyone, whether or not they are a Snowflake customer, via reader accounts that can be created straight from the user interface. The provider can use this feature to create and maintain a Snowflake account for a customer.

There isn't much to write about in terms of drawbacks.

Conclusion

These days, the Snowflake data warehouse is gaining a lot of traction, and learning it proves to be more productive than traditional-based solutions. By incorporating Snowflake into their operations, companies enhance their performance.

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Last updated: 14 November 2022
About Author
Madhuri Yerukala

Madhuri is a Senior Content Creator at MindMajix. She has written about a range of different topics on various technologies, which include, Splunk, Tensorflow, Selenium, and CEH. She spends most of her time researching on technology, and startups. Connect with her via LinkedIn and Twitter .